97,782 research outputs found
Caching in Multidimensional Databases
One utilisation of multidimensional databases is the field of On-line
Analytical Processing (OLAP). The applications in this area are designed to
make the analysis of shared multidimensional information fast [9]. On one hand,
speed can be achieved by specially devised data structures and algorithms. On
the other hand, the analytical process is cyclic. In other words, the user of
the OLAP application runs his or her queries one after the other. The output of
the last query may be there (at least partly) in one of the previous results.
Therefore caching also plays an important role in the operation of these
systems. However, caching itself may not be enough to ensure acceptable
performance. Size does matter: The more memory is available, the more we gain
by loading and keeping information in there. Oftentimes, the cache size is
fixed. This limits the performance of the multidimensional database, as well,
unless we compress the data in order to move a greater proportion of them into
the memory. Caching combined with proper compression methods promise further
performance improvements. In this paper, we investigate how caching influences
the speed of OLAP systems. Different physical representations (multidimensional
and table) are evaluated. For the thorough comparison, models are proposed. We
draw conclusions based on these models, and the conclusions are verified with
empirical data.Comment: 14 pages, 5 figures, 8 tables. Paper presented at the Fifth
Conference of PhD Students in Computer Science, Szeged, Hungary, 27 - 30 June
2006. For further details, please refer to
http://www.inf.u-szeged.hu/~szepkuti/papers.html#cachin
Towards a query language for annotation graphs
The multidimensional, heterogeneous, and temporal nature of speech databases
raises interesting challenges for representation and query. Recently,
annotation graphs have been proposed as a general-purpose representational
framework for speech databases. Typical queries on annotation graphs require
path expressions similar to those used in semistructured query languages.
However, the underlying model is rather different from the customary graph
models for semistructured data: the graph is acyclic and unrooted, and both
temporal and inclusion relationships are important. We develop a query language
and describe optimization techniques for an underlying relational
representation.Comment: 8 pages, 10 figure
Differentiated Multiple Aggregations in Multidimensional Databases
International audienceMany models have been proposed for modeling multidimensional data warehouse and most consider a same function to determine how measure values are aggregated according to different data detail levels. We provide a conceptual model that supports (1) multiple aggregations, associating to the same measure a different aggregation function according to analysis axes or hierarchies, and (2) differentiated aggregation, allowing specific aggregations at each detail level. Our model is based on a graphical formalism that allows controlling the validity of aggregation functions (distributive, algebraic or holistic). We also show how conceptual modeling can be used, in an R-OLAP environment, for building lattices of pre-computed aggregates
Implementation of the Multidimensional Modeling Concepts into Object-Relational Databases
A key to survival in the business world is being able to analyze, plan and react to changing business conditions as fast as possible. With multidimensional models the managers can explore information at different levels of granularity and the decision makers at all levels can quickly respond to changes in the business climate-the ultimate goal of business intelligence. This paper focuses on the implementation of the multidimensional concepts into object-relational databases.e-business, database
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